Articles | Volume 16, issue 8
https://doi.org/10.5194/essd-16-3705-2024
https://doi.org/10.5194/essd-16-3705-2024
Data description paper
 | 
16 Aug 2024
Data description paper |  | 16 Aug 2024

A 100 m gridded population dataset of China's seventh census using ensemble learning and big geospatial data

Yuehong Chen, Congcong Xu, Yong Ge, Xiaoxiang Zhang, and Ya'nan Zhou

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Cited articles

Baynes, J., Neale, A., and Hultgren, T.: Improving intelligent dasymetric mapping population density estimates at 30 m resolution for the conterminous United States by excluding uninhabited areas, Earth Syst. Sci. Data, 14, 2833–2849, https://doi.org/10.5194/essd-14-2833-2022, 2022. 
Bright, E. A. and Coleman, P. R.: LandScan: a global population database for estimating populations at risk, Photogramm. Eng. Rem. S., 66, 849–858, 2000. 
Chen, M., Xian, Y., Huang, Y., Zhang, X., Hu, M., Guo, S., Chen, L., and Liang, L.: Fine-scale population spatialization data of China in 2018 based on real location-based big data, Scientific Data, 9, 624, https://doi.org/10.1038/s41597-022-01740-5, 2022. 
Chen, Q., Hou, X., Zhang, X., and Ma, C.: Improved GDP spatialization approach by combining land-use data and night-time light data: a case study in China's continental coastal area, Int. J. Remote Sens., 37, 4610–4622, 2016. 
Chen, Q., Ye, T., Zhao, N., Ding, M., Ouyang, Z., Jia, P., Yue, W., and Yang, X.: Mapping China's regional economic activity by integrating points-of-interest and remote sensing data with random forest, Environment and Planning B: Urban Analytics and City Science, 48, 1876–1894, https://doi.org/10.1177/2399808320951580, 2021. 
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Short summary
Population data is crucial for human–nature interactions. Gridded population data can address limitations of census data in irregular units. In China, rapid urbanization necessitates timely and accurate population grids. However, existing datasets for China are either outdated or lack recent census data. Hence, a novel approach was developed to disaggregate China’s seventh census data into 100 m population grids. The resulting dataset outperformed the existing LandScan and WorldPop datasets.
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